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    Databases

    A tantárgy neve magyarul / Name of the subject in Hungarian: Adatbázisok

    Last updated: 2018. május 25.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics
    Course ID Semester Assessment Credit Tantárgyfélév
    VITMAB04 3 2/1/1/v 5  
    3. Course coordinator and department Dr. Gajdos Sándor,
    4. Instructors Dr. Gajdos, Sándor, Department of Telecommunications and Media-informatics
    5. Required knowledge Basic technical knowledge about programming languages, data structures
    6. Pre-requisites
    Kötelező:
    [ HA EgyenCsoportTagja("INFO - 2022 - MINTATANTERV HALLGATÓI")

    AKKOR
    TárgyTeljesítve_Képzésen("BMEVISZAA04")
    EGYÉBKÉNT

    ((TárgyEredmény( "BMEVISZAA01" , "aláírás" , _ ) = -1
    VAGY TárgyEredmény( "BMEVISZAA04" , "aláírás" , _ ) = -1
    VAGY TárgyEredmény( "BMEVISZA110" , "aláírás" , _ ) = -1)

    ÉS NEM ( TárgyEredmény( "BMEVITMA311", "jegy" , _ ) >= 2
    VAGY TárgyEredmény("BMEVITMA311", "FELVETEL", AktualisFelev()) > 0
    VAGY TárgyEredmény( "BMEVITMAB00", "jegy" , _ ) >= 2
    VAGY TárgyEredmény("BMEVITMAB00", "FELVETEL", AktualisFelev()) > 0
    VAGY TárgyEredmény( "BMEVITMAB00" , "aláírás" , _ ) = -1
    VAGY TárgyEredmény( "BMEVITMA311" , "aláírás" , _ ) = -1
    VAGY TárgyEredmény( "BMEVITMA308", "jegy" , _ ) >= 2
    VAGY TárgyEredmény("BMEVITMA308", "FELVETEL", AktualisFelev()) > 0
    VAGY TárgyEredmény( "BMEVITMAB02", "jegy" , _ ) >= 2
    VAGY TárgyEredmény("BMEVITMAB02", "FELVETEL", AktualisFelev()) > 0 ) ) ]

    ÉS

    (Training.Code=("5N-A8")
    VAGY Training.Code=("5NAA8") )

    VAGY EgyenCsoportTagja("Kreditpótlás_2023/24/2 ")

    A fenti forma a Neptun sajátja, ezen technikai okokból nem változtattunk.

    A kötelező előtanulmányi rend az adott szak honlapján és képzési programjában található.

    7. Objectives, learning outcomes and obtained knowledge To make students familiar with the operation and usage of database management systems. Application of the theory also in the engineering practice focusing on relational systems.
    8. Synopsis
    • Data and information, structured, non-structured and semistructured data
    • Database management systems, components, operation
    • Data Definition Language, Data Manipulation Language, Host language
    • Layered model of DBMS, principle of data independence
    • Data models, data modelling.
    • Entity-relationship model/diagram, attributes, relationship-types, constraints, specialization, weak entity sets.
    • Relational data model, relational algebra
    • Design of relational schemes from E/R diagram
    • Physical data organization: heap, hash, indexing (sparse, dense) (flat, multilevel)
    • Tuple relational calculus, domain relational calculus, safe expressions.
    • Functional dependencies, key, superkey, candidate key
    • Normal forms of 0NF, 1NF, 2NF, 3NF, BCNF
    • Fundamentals of transaction management
    Laboratory synopsis:
    • Getting to know a relational database management system
    • Definition of relational schemes in SQL
    • Database queries in SQL
    • Manipulation of data in SQL
    • XML-based data management

    9. Method of instruction

    Interactive lectures in a small group with built-in practices. 

    The laboratories are scheduled biweekly. Individual preparation is needed for the labs from the specific materials provided by the tutor, then consultation, working on the predefined tasks in the computer laboratory of the university under the supervision of the tutor. The students may finish their tasks and the laboratory report at home as well.

    10. Assessment
    1. In the teaching period: 5-6 midterm tests, similar to real, numerical engineering problems. Scoring: from 1 to 5, 1 is the weakest grading. In case of any serious or fundamental mistake, the grading will be 1.

    2. Laboratory: each laboratory practice must be completed at least on passed level.The laboratory practices will be graded based on the a) preparation of the student b) activity during the lab c) quality of the laboratory report.

    3. Condition for the signature is passing the tests in average and all of the laboratory practices must be satisfactory at least.

       

    4. In the exam's period: written exam, similar to the problems of the midterm tests. Scoring condition for successful exam is at least 40%. Below 40% the exam is unsuccessful. Calculation of the final grade: 30% Laboratory average + 70% written exam.
    11. Recaps

    Accordig to the Code of Studies and Exams.

    Only one laboratory practice can be repeated during the semester if the student failed or missed the lab. 
    12. Consultations Individual consultation: upon agreement with the lecturer.
    13. References, textbooks and resources Recommended books:
    • Silberschatz, H. F. Korth, S. Sudarshan: Database System Concepts, 6th Edition, 2010.
    • Ullman: Principles of Database and Knowledge-Base Systems, Comp. Sci. Press vol. I-II, 1990.
    • Ullman-Widom: First Course in Database Systems, 2007.
    For the labs:
    • Syllabi provided by the tutor
    • Web pages identified by the tutor
    14. Required learning hours and assignment
    Kontakt óra56
    Félévközi készülés órákra10
    Felkészülés zárthelyire14
    Házi feladat elkészítése16
    Kijelölt írásos tananyag elsajátítása14
    Vizsgafelkészülés40
    Összesen150
    15. Syllabus prepared by Dr. Gajdos, Sándor, h.ass.prof.